5G MEC-Enhanced C-2V2X for Intersection Management
Dr. Duminda Wijesekera
KEY INTERESTS
Intelligent transportation systems; NextG-based Edge services; Smart building and smart city infrastructure; Digital twin development; Defensive and offensive cyber operations
APPOINTMENTS/AFFILIATIONS
Professor, Department of Computer Science, Department of Cybersecurity Engineering, George Mason University
Chief Science & Technology Officer, GAIL
Fellow, Commonwealth Cyber Initiative
ACADEMIC DEGREES
PhD, Computer Science, University of Minnesota
PhD, Mathematical Logic, Cornell University
5G MEC-ENHANCED C-V2X FOR INTERSECTION MANAGEMENT
This reseach addresses the grand challenge of designing, developing, and testing the next-generation of safe, connected, and autonomous intersection management leveraging Mobile Edge Computing (MEC)-based and situationally-aware ultra-reliable low-latency communications (URLLC) at intersections. The economic impact of autonomous intersection mangement is significant. For example, the Northern Virginia region maintains about 1700 signalized intersections (at an approximate cost of $300,000/each), requiring manual servicing and reprogramming to synchronize signals. Moving them to a 5G-MEC enables manual tasks to take place via cloud services. Having replicated MECs provides resilience against system failure and allows the designers to execute what if conditions using realistic traffic simulators. Additionally, many V2X accidents happen at intersections. Thus, all-actor encompassing MEC-enhanced low information latency communications for autonomous intersection management reduces these accidents and incidents (i.e., near-accidents).